Assessing Organizational Users’ Intentions and Behavior to AI Integrated CRM Systems: a Meta-UTAUT Approach

2023 | Information Systems Frontiers | Citations: 0

Authors: Chatterjee, Sheshadri; Rana, Nripendra P.; Khorana, Sangeeta; Mikalef, Patrick; Sharma, Anuj

Abstract: This paper tests the meta-analysis based unified theory of acceptance and use of ... Expand

Abstract: This paper tests the meta-analysis based unified theory of acceptance and use of technology (meta-UTAUT) model to predict the behavioral intentions of organizational users and their use behavior to artificial intelligence (AI) integrated customer relationship management (CRM) systems. Data was collected from 315 organizational users in India. The hypotheses draw on the theoretical underpinnings which have been statistically validated. Results show that CRM quality and satisfaction significantly influences an organization’s employees attitudes and intentions to use AI integrated CRM systems. The compatibility of CRM systems has, however, a limited impact on employees attitudes. The findings, which are aligned with the extended UTAUT model, provide useful insights into organizations and decision-makers for designing AI integrated CRM systems. Collapse

Topics: artificial intelligence customer relationship management system behavioral intention usage intention social influence

Methods: survey partial least squares path modeling partial least squares regression mediation analysis theoretical contribution

Theories: unified theory of acceptance and use of technology

Navigating the Paradox of IT Novelty and Strategic Conformity: The Moderating Role of Industry Dynamism

2023 | International Conference on Information Systems | Citations: 0

Authors: Chaturvedi, Devina; Kathuria, Abhishek; Andrade, Mariana; Saldanha, Terence

Abstract: Although achieving strategic distinctiveness is critical for firms in dynamic i ... Expand

Abstract: Although achieving strategic distinctiveness is critical for firms in dynamic industries, where the competitive landscape and market conditions frequently change, there is a paucity of research on the impact of information technology (IT) on a firm's strategic conformity (or distinctiveness). Motivated by the importance of strategic conformity and emergence of novel technologies, we draw on institutional theory and hypothesize that IT Novelty positively impacts strategic conformity. Second, drawing on resource-based view, we hypothesize that market dynamism and competitive dynamism negatively moderate the effect of IT Novelty on strategic conformity. Third, we hypothesize that the moderating impact is stronger for market dynamism than competitive dynamism. We find support for our hypotheses using a fifteen-year dataset from over 300 U.S. manufacturing firms. Our study contributes to theory and managerial practice by combining institutional and resource-based view perspectives to examine how IT Novelty shapes a firm's strategic conformity, particularly in dynamic industry conditions. Collapse

Topics: database system decision making artificial intelligence internet of things mobile system

Methods: longitudinal research autocorrelation analysis hierarchical linear modeling robustness check regression analysis method

Theories: resource based view of the firm institutional theory

Token Incentives in a Volatile Crypto Market: The Effects of Token Price Volatility on User Contribution

2023 | Journal of Management Information Systems | Citations: 0

Authors: Chen, Kun; Fan, Yifan; Liao, Shaoyi Stephen

Abstract: Crypto tokens, issued and managed via smart contracts, function as rewards in bl ... Expand

Abstract: Crypto tokens, issued and managed via smart contracts, function as rewards in blockchain systems to encourage user participation. Distinct from monetary incentives, token incentives are uncertain in reward magnitude due to the large swings in token prices on crypto markets. By focusing on token price volatility, this study investigates how the reward uncertainty affects user contribution in a tokenized digital platform. Our empirical setting is Steemit, a platform where bloggers write posts and share token rewards based on their posts' popularity. We find that while high token price volatility induces a large volume of blog posts, it diminishes post quality. The dichotomous effects are explained via two mechanisms: users' direct reactions to reward uncertainties and their indirect reactions, mediated by altered token preference amid volatility shocks. Deeply exploring this dynamic process, our results reveal that token price volatility facilitates a platform's network short-term effect but impairs long-term user creativity. Our empirical findings thus extend the literature on blockchain economics and cryptocurrencies and have practical implications for the design of incentive mechanisms on tokenized digital platforms. Collapse

Topics: blog blockchain digital platform cryptocurrency user behavior

Methods: longitudinal research instrumental variables estimation data transformation principal component analysis vector autoregression

Theories: motivation crowding theory

Factors Affecting the Use of Blockchain Technology in Humanitarian Supply Chain: A Novel Fuzzy Large-Scale Group-DEMATEL

2023 | Group Decision and Negotiation | Citations: 0

Authors: Chen, Lu; Hendalianpour, Ayad; Feylizadeh, Mohammad Reza; Xu, Haiyan

Abstract: Based on previous evidence, the use of blockchain for improving Supply Chains (S ... Expand

Abstract: Based on previous evidence, the use of blockchain for improving Supply Chains (SCs) regarding humanitarian projects has received attention over the past five years. The present study is innovative in investigating crucial parameters affecting the using of Blockchain Technology (BT) in Humanitarian Supply Chains (HSCs). More precisely, this study emphasizes parameters that affect blockchain in the HSCs and presents a new fuzzy large-scale group decision-making trial and evaluation laboratory (fuzzy large-scale group-DEMATEL) approach to analyze the interdependence of contributing factors for using BT in HSCs. This method consists of two stages: (1) clustering the large-scale group-experts into small subgroups by their characteristics, and (2) identifying the key factors affecting BT in HSCs with a novel fuzzy large-scale group-DEMATEL approach. According to experts, in this study, among the 25 evaluated factors, disintermediation has been identified as the most important one, followed by anonymity and security. A closer look reveals that 13 and 12 factors have been “cause” and “effect” factors, respectively. Our research can be used to promote the effectiveness of using BT in HSCs, so as to promote the proper distribution of relief materials in practical disasters. Collapse

Topics: blockchain database system risk management anonymity decision making

Methods: cluster analysis computational algorithm cross sectional research literature study

Theories: fuzzy set theory

The Relationship Between Twitter Sentiment and Stock Performance: A Decision Tree Approach

2023 | HICSS | Citations: 0

Authors: Chen, Rongjuan; Dong, Ruoxi

Abstract: Social media has become a communication tool, but also a valuable database for r ... Expand

Abstract: Social media has become a communication tool, but also a valuable database for researchers and practitioners to gather information, share knowledge, as well as express opinions about stock performance. The sentiment embedded in social media content can be analyzed to predict stock performance. Although numerous past studies have attempted to predict stock price movement using social media sentiment, some emerging analytical tools, like existing lexicons, may require further testing and validation in a financial decision making context. In this study, we develop and test predictive models for stock price and trend forecasting. By using a large-scale sample of tweets collected from Twitter, related to four companies, Apple, Google, Microsoft, and Netflix, we propose a novel decision tree approach to stock performance prediction. Based on our findings, we then provide theoretical and practical implications and discuss the directions for future work. Collapse

Topics: Twitter social media decision making digital service Netflix

Methods: sentiment analysis decision tree classification regression analysis method multiple linear regression NLP tool

Theories: behavioral economics

The bright side of emotional extremity: Evidence from tipping in live streaming platform

2023 | Information & Management | Citations: 0

Authors: Chen, Xingyu; Ji, Li; Jiang, Ling; Huang, Justin T.

Abstract: Live streaming has enabled viewers to interact with broadcasters and peer viewer ... Expand

Abstract: Live streaming has enabled viewers to interact with broadcasters and peer viewers, as well as tip the broadcaster based on their emotional state. While most tips are small, a minority of viewers tip extremely large. To uncover such unique tipping patterns, we draw on the emotion literature and competitive arousal theory to examine how viewers’ emotional extremity affects tipping behavior and how broadcaster’s emotional response moderates the baseline effect. This study contributes to the emerging live streaming literature by revealing the differential effects of emotional extremity on tipping amount and frequency and provides practical implications for broad­ casters and platforms to steer tipping behavior. Collapse

Topics: live streaming platform marketing management accounting digital platform artificial intelligence

Methods: statistical hypothesis test computational algorithm psychometrics machine learning longitudinal research

Trust and deception with high stakes: Evidence from the friend or foe dataset

2023 | Decision Support Systems | Citations: 0

Authors: Chen, Xunyu; Wang, Xinran; Spitzley, Lee; Nunamaker, Jay

Abstract: Many social interactions rely on the premise of mutual trust, but deception viol ... Expand

Abstract: Many social interactions rely on the premise of mutual trust, but deception violates trust and poses risk. Empirically examining trust and deception, particularly in high-stakes situations, is challenging but essential for improving the research realism and generalizability. To address this difficulty, we study trusting and deceptive behaviors in a high-stakes situation by using a novel dataset created from an American game show, Friend or Foe (FoF). In the show, a contestant's reward was determined through a trust game modified from the prisoner's dilemma. We explore how numerous human behaviors including facial expressions, gaze, head pose, body motion, language, and socio-demographic attributes, were related to a contestant's trusting or deceptive decision. Using a data-driven approach, we find that the deceivers' (contestants who chose Foe) behavior featured a neutralized face, negative facial emotions, enhanced upper body motion, and language with a lower sense of immediacy and agreeableness. The contestants who chose to trust (chose Friend) exhibited opposite behavioral patterns. Socio-demographic factors such as age, height, and facial attractiveness were also associated with a contestant's choice. Combining multimodal information, machine learning classifiers could predict the contes­ tant's choice with an accuracy about 25% greater than earlier reported human accuracy. We contribute to both trust and deception literature by examining the generalizability of trusting and deceptive behaviors to a new high-stakes scenario. We also add to the decision support literature by showing the superior predictive perfor­ mances of combining behavioral and socio-demographic features. Furthermore, we contribute to the academic community by introducing the FoF dataset. Collapse

Topics: decision support website YouTube Python decision making

Methods: meta analysis support vector machine correlation analysis descriptive statistic random forest classification

The Cost of Free: The Effects of “Wait-for-Free” Pricing Schemes on the Monetization of Serialized Digital Content

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Choi, Angela; Rhee, Ki-Eun; Yoon, Chamna; Oh, Wonseok

Abstract: Leveraging a combination of analytical frameworks and empirical assessments, th ... Expand

Abstract: Leveraging a combination of analytical frameworks and empirical assessments, this study investigates the effects of wait-for-free (WFF) pricing schemes on the monetization of serialized, digital entertainment content, which has become increasingly pervasive on online platforms. WFF pricing is a strategy in which consumers are given the option to either wait a certain amount of time to acquire digital content at no cost or pay to consume it immediately. We evaluate the extent to which habit formation and presentbiased preferences driven by the consumption of addictive stock affect individual consumers' willingness to wait (or pay) for content, which, in turn, determines the efficacy of WFF pricing. We also examine the conditions under which consumers switch from waiting for free content to instantaneously purchasing content. Our findings indicate that WFF pricing increases the sales of serialized digital content, generating new demand from customers who would otherwise forgo participation in the market. In addition, the pricing design effectively generates sustained profits in the long run. We found that most consumers who initiate a purchase either upon initial market entry or upon switching continue to purchase as new episodes become available. Moreover, the results indicate that as a user accumulates free episodes of a specific series, given extended waiting periods, the likelihood of their conversion from a wait-for-free customer to an instant-purchase customer increases. In particular, WFF pricing effectively augments the willingness to pay of low-valuation consumers as habit formation builds up through time with the free consumption of serialized content. One free episode can elevate the likelihood of consumer purchase by up to 13%. However, as the number of free episodes consumed goes beyond a threshold, the likelihood of conversion decreases. We conclude with a discussion of managerial implications that can help content providers monetize their serialized digital content products. Collapse

Topics: price management consumer behavior advertising management digital good customer satisfaction

Methods: mathematical model robustness check econometric modeling proportional hazards model survival analysis

Theories: behavioral economics

The Crisis in Local Newspapers and Organizational Wrongdoing: The Role of Community Social Connectedness

2023 | Organization Science | Citations: 0

Authors: Choi, Tony Jaehyun; Valente, Mike

Abstract: Drawing on institutional anomie theory, we examine how the crisis in local newsp ... Expand

Abstract: Drawing on institutional anomie theory, we examine how the crisis in local newspapers has induced organizational wrongdoings in local communities. We argue that, because local newspapers are the primary source of accountability journalism in local communities, their decline leads to an anomic state that increases the scale of organizational wrongdoing. We also investigate whether institutional complementarity helps overcome the anomic state: Due to functional similarity, community social connectedness compensates for the scarcity of local newspapers. Our analysis of U.S. metropolitan areas for the period of 2007–2015 reveals that the positive relationship between local newspaper scarcity and the scale of organizational wrongdoing is not present in all communities but does appear when a community lacks community social connectedness. We also find that this moderating role of community social connectedness is observed only for internal organizational wrongdoings that are less visible to the public than external ones. Collapse

Topics: digital news missing data decision making social capital database system

Methods: descriptive statistic statistical hypothesis test longitudinal research longitudinal data analysis hierarchical linear modeling

Theories: organizational behavior theory

How much is too much? The nonlinear link between emotional arousal and review helpfulness

2023 | Decision Support Systems | Citations: 0

Authors: Chou, Yen-Chun

Abstract: Online reviews affect consumer purchase decisions and become prevalent in differ ... Expand

Abstract: Online reviews affect consumer purchase decisions and become prevalent in different sectors. Platforms elicit useful reviews by allowing consumers to vote for helpfulness. The link between review features and review helpfulness hence has been a topic of broad interest in information systems (IS) and Internet commerce. Psy­ chological science studies show that expressed emotions in information – valence and arousal significantly in­ fluence receivers’ engagement and valuation. Unlike valence (negative or positive) that is widely-analyzed, emotional arousal is a less-studied attribute of online reviews. This study presents a careful account of the nonlinear link between emotional arousal and review helpfulness. Following a rigorous procedure of theorizing and testing nonlinear relationships (Haans et al. 2016), we articulate latent mechanisms leading to an inverted Ushaped association and how valence would moderate the nonlinear effect of review arousal. We analyze reviews on experience goods from Yelp.com and find firm support for our hypotheses. The findings are triangulated using reviews on search goods from Amazon.com. While the nonlinear effect of review arousal and interactions with review valence are robust to both types of goods, an alternative moderation path of review valence on the inverted U-shaped relationship is observed. Our empirical study contributes to the literature by shedding lights on the dynamics among arousal, valence, review helpfulness, and product types, which illustrates a prototypical example to IS/e-commerce scholars on rigorously conceptualizing and estimating U-shaped links as well as their moderations. Collapse

Topics: tablet experience good online review user-generated content electronic commerce

Methods: theory development product review triangulation sentiment analysis reference modelling